Mycoplasma genitalium, the cell division gene cluster is limited to four genes: mraZ, mraW, MG_223, and ftsZ. In a previous study, we demonstrated that ftsZ was dispensable for growth of M. genitalium under laboratory culture conditions. Herein, we show that the entire cell division gene cluster of M. genitalium is non-essential for growth in vitro. Our analyses indicate that loss of the mraZ gene alone is more detrimental for growth of M. genitalium than deletion of ftsZ or the entire cell division gene cluster. Transcriptional analysis revealed a marked upregulation of ftsZ in the mraZ mutant. Stable isotope labeling by amino acids in cell culture (SILAC)-based proteomics confirmed the overexpression of FtsZ in MraZ-deprived cells. Of note, we found that ftsZ expression was upregulated in non-adherent cells of M. genitalium, which arise spontaneously at relatively high rates. Single cell analysis using fluorescent markers showed that FtsZ localization varied throughout the cell cycle of M. genitalium in a coordinated manner with the chromosome and the terminal organelle (TMO). In addition, our results indicate a possible role for the RNA methyltransferase MraW in the regulation of FtsZ expression at the post-transcriptional level. Altogether, this study provides an extensive characterization of the cell division gene cluster of M. genitalium and demonstrates the existence of regulatory elements controlling FtsZ expression at the temporal and spatial level in mycoplasmas.It is well-established that FtsZ drives peptidoglycan synthesis at the division site in walled bacteria. However, the function and conservation of FtsZ in wall-less prokaryotes such as mycoplasmas are less clear. In the genome-reduced bacterium  Organization and length of the dcw gene cluster are exquisitely conserved across phylogenetically distant species. As an exception, several genes that lie within the dcw gene cluster of Gram-negative and Gram-positive rods, are located elsewhere in the chromosome in Gram-positive cocci . Chloramphenicol (17μgml−1) or tetracycline (3μgml−1) were added for mutant selection. All M. genitalium strains used in this work are listed in the Escherichia coli strain XL-1 Blue was used for cloning and plasmid propagation. The strain was grown in Luria Bertani (LB) or LB agar plates containing 100μgml−1 ampicillin, 40μgml−1 X-Gal, and 24μgml−1 Isopropyl β-D-1-thiogalactopyranoside (IPTG) when needed.All M. genitalium transformation were obtained using the GenElute HP Midiprep kit (Sigma).Plasmid DNA was obtained using 5Prime kit. PCR products were purified from agarose gels using Nucleospin Gel and PCR Clean-up kit (Macherey-Nagel) and digested with the corresponding restriction enzymes (Fermentas) when necessary. All primers used in this study are listed in the M. genitalium was carried out as previously described (−1), and incubation for 1h at 37°C followed by inactivation at 95°C for 10min.A detailed explanation of the methodology, including primers and plasmids, used to generate the different mutants created in this study is supplied in the escribed . ScreeniM. genitalium lysate, following manufacturer’s instructions. All reactions were analyzed in an ABI PRISM 3130xl Genetic Analyzer at the Servei de Genòmica i Bioinformàtica (UAB).DNA sequencing reactions were performed using BigDye® v3.1 Cycle Sequencing kit using 2.5μl of genomic DNA or M. genitalium cultures were determined using an adaptation of the colorimetric protocol described by 2 flasks with 5ml SP4. Attached cells were scraped off, recovered by centrifugation at 12,000rpm, and resuspended in 3ml of fresh SP4. Then, 300μl of the cellular suspension were inoculated in four different wells of a 96-well plate. Each of these wells constitutes the first sample of four technical repeats. About 100μl of the first well (sample 1) were inoculated into the next well (sample 2) already containing 200μl of fresh SP4, thus diluting 1/3 the initial concentration. This process was repeated four more times , achieving a final dilution of 1/243. The 96-well plate was sealed with transparent tape, placed into a Tecan Sunrise Absorbance Microplate Reader (Tecan), and incubated at 37°C for 7days. As M. genitalium grows, the bacterial metabolism acidifies the culture medium changing the color of the phenol red indicator from red (pH 7.8) to yellow (pH 6), which was detected by measuring the absorbance at 550nm. For each analysis, readings were taken every 30min for up to 8days . The readings were stored in an Excel datasheet and analyzed once the experiment was completed, and a curve was plotted for each dilution and the inflection point was inferred. Next, the inflection points were plotted in a graphic, using the Napierian logarithm of the dilution as the x coordinate for each dilution. Once all the inflection points were plotted, the slope  was inferred by linear regression, and the doubling time (g) was obtained and according to the general equation for exponential growth of bacteria [g=ln2/(1/μ)].Growth rates of M. genitalium were scraped off in 1ml of fresh SP-4 and reinoculated in two new 25cm2 tissue culture flasks with fresh SP-4 medium for 6h. Then, cells were lysed, and total RNA was extracted using the miRNeasy Mini Kit (Qiagen). RNA libraries were prepared with TruSeq Stranded Total RNA Library Prep Kit (Illumina) and analyzed using a HiSeq 3000 System (Illumina) at the Genomics Unit from the Centre for Genomic Regulation (CRG), Barcelona. cDNA clusters were immobilized in sequencing lanes of 2×50 reads. Reverse and complementary were computed for sequences coming from Read1 primer. Data analysis and sequence alignment were performed using Bowtie2  and then treated with Turbo DNase (Thermo Fisher Scientific) following the manufacturer’s instructions. Reverse transcription was performed with iScript Reverse Transcriptase (Bio-Rad) and random primers as previously described  or heavy (13C) lysine. Once grown, cells were split (1:10) and cultured in the same conditions. Then, cells were washed with PBS, scraped off, and pellets stored at −80°C. Protein lysates were prepared as previously described (4HCO3 and digested with 5μg LysC (Wako) overnight at 37°C. Finally, the peptide mix was acidified with formic acid and desalted with a homemade Empore C18 column  mode and full MS scans with one micro scan at a resolution of 60,000 were used over a mass range of m/z 350–2,000 with detection in the Orbitrap. Auto gain control (AGC) was set to 106, and dynamic exclusion (60s) and charge state filtering disqualifying singly charged peptides were carried out. In each cycle of DDA analysis, following each survey scan, the top 10 most intense ions with multiple charged ions above a threshold ion count of 5,000 were selected for fragmentation at normalized collision energy of 35%. Fragment ion spectra produced via collision-induced dissociation (CID) were acquired in the ion trap, AGC was set to 5e4, with an isolation window of 2.0 m/z, activation time of 0.1ms, and maximum injection time of 100ms. All data were acquired with Xcalibur software v2.2. The MaxQuant software suite (v1.4.0.5) was used for peptide identification and SILAC protein quantitation . To this end, escribed . Proteintitation . The datMycoplasma genitalium cultures were grown to mid-log phase over glass coverslips. Samples were fixed, dehydrated, and critical point dried as previously described  on IBIDI chamber slides for 16h, washed once with 1×PBS, and visualized on an inverted Nikon Eclipse TE 2000-E microscope. For the analysis of the mg191ftsZCh non-adherent mutant, IBIDI chamber slides were previously treated with 0.2mg/ml poly-l-lysine hydrobromide (Sigma-Aldrich) solution, allowing surface adherence. In addition, cells were passed 10 times through a 25-gauge syringe to break the aggregates. Hoechst 33342 0.01mgml−1 was added when necessary. All strains were grown and visualized under the same conditions. Phase contrast, enhanced yellow fluorescent protein (eYFP), 4',6-diamidino-2-phenylindole (DAPI), and TRITC epifluorescence images were captured with a Digital Sight DS-SMC Nikon camera controlled by NIS-Elements BR software. Images were analyzed using ImageJ software and GDSC plug-in.ftsZ gene was non-essential in M. genitalium  than that of the wild-type strain  as compared to the wild-type strain  was comparable to that of the wild-type strain  than those of the wild-type strain , indicating that the absence of MraW is also detrimental for growth. All the mutant strains obtained were examined by genome resequencing for the presence of mutations other than those introduced by genetic manipulation. No major genome rearrangements like large deletions or translocations were detected in all the analyzed strains. However, all the strains showed the presence of small variants like SNPs or INDELS in different frequencies. Many of these variants were also identified in the G37 strain. All new variants were found in recombinogenic, variable repeated regions, being most of them in non-coding genome locations, thus supporting the absence of additional mutations that could impact on the phenotype of the dcw strains  when compared to the wild-type (13.35%) or the mraREF strains . Moreover, we observed that cytokinetic cells from the mraZ mutant were markedly elongated  than those of the wild-type strain , a key component of the Min system of B. subtilis  BioProject database under accession number PRJNA750275.CM-T, ST-P, ML-S, LS, EQ, JP, and OQP contributed to conception and design of the study. CM-T, ST-P, MM-S, MH-R, CM-N, ML-S, and OQP performed the experiments. CM-T and ST-P performed the statistical analysis. CM-T and OQP wrote the first draft of the manuscript. ST-P, EQ, and JP wrote some parts of the manuscript. All authors contributed to the article and approved the submitted version.This work was supported by the grant BIO2017-84166-R from the Ministerio de Ciencia, Innovación y Universidades.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Nevertheless, highly structured circRNAs are preferentially retained in leukocytes. Differential expression analysis reports significant differences in circRNA and linear RNA expression between MS patients and controls, as well as between different MS types. (4) Conclusions: Plasma derived EV RNA cargo is not a representation of leukocytes’ cytoplasm but a message worth studying. Moreover, our results reveal the interest of circRNAs as part of this message, highlighting the importance of further understanding RNA regulation in MS.(1) Background: Extracellular vesicles (EVs) are released by most cell types and are implicated in several biological and pathological processes, including multiple sclerosis (MS). Differences in the number and cargo of plasma-derived EVs have been described in MS. In this work, we have characterised the EV RNA cargo of MS patients, with particular attention to circular RNAs (circRNAs), which have attracted increasing attention for their roles in physiology and disease and their biomarker potential. (2) Methods: Plasma-derived EVs were isolated by differential centrifugation , and RNA-Sequencing was used to identify differentially expressed linear and circRNAs. (3) Results: We found differences in the RNA type distribution, circRNAs being enriched in EVs vs. leucocytes. We found a number of (corrected  Extracellular vesicles (EVs) are membrane-coated particles of endosomal or plasma membrane origin that are secreted to the extracellular environment. Almost all cell types release EVs, both in physiological and pathological conditions, and they can be isolated from plasma and other bodily fluids. They play an essential role in indirect cell-to-cell communication, as their proteins, lipids and nucleic acids can be transferred between cells . This EVMS is a chronic autoimmune disease of the central nervous system (CNS) leading to demyelination. Consequently, it is associated with axonal and neuronal degeneration, resulting in neurological disability. It affects more than 2.5 million people worldwide and it is mainly diagnosed in young adults between 20 and 40 years ,7, a pheDifferent clinical forms of the disease are distinguished. For most of the patients about 85%), the early phase of the disease is relapsing–remitting MS or RR-MS. RR-MS is characterized by clinical exacerbations, or relapses, caused by autoreactive immune cells that enter the CNS, resulting in focal inflammation and demyelination that produces neurological symptoms. After these relapses, which last at least 24 h, the inflammation resolves and partial remyelination occurs, entering a phase named remission. With time, for many RR-MS patients, the recovery starts to be incomplete, leading to disability accumulation. This later phase of the disease is characterized by less relapses but a progressive accumulation of disability, and is named secondary progressive MS (SP-MS). For the other 10–15% of the patients, the disease progresses from the onset with no apparent relapses, a course known as primary progressive or PP-MS 5%, the e,10.Studies on EVs in MS patients have revealed a general change in their number and cargo when compared to controls, but also in relapse and in response to treatments ,12,13. ISeveral components of the RNA cargo have been studied in different diseases including MS, revealing their importance in diagnosis  as well CircRNAs are formed by an alternative splicing process called backsplicing, by which a downstream splice donor and upstream splice acceptor are joined together. The resulting covalently closed circular transcripts are characterized by the lack of free ends and the presence of a circRNA-exclusive junction called back-splice junction (BSJ). Their circular structure endows them with their high stability, which along with their presence in different biofluids, their cell- or tissue-specific expression and their evolutionary conservation, has attracted the interest of many researchers ,21. ThesIn fact, circRNAs have been detected in EVs of bodily fluids from different pathological conditions, and have been found to play a role in processes such as drug resistance, metastasis or cell proliferation . Most stIn this work, we have characterized the transcriptomic profile of EVs in MS patients and healthy controls, including for the first time the characterization of circRNAs and a preliminary study of their potential functions in the disease. Moreover, we have compared some of the features of the EV transcriptome with the transcriptome in leukocytes from MS patients and healthy controls recently described by our group .www.biobancovasco.org, last accessed on 1 March 2019).For the study of EV transcriptome, whole blood was obtained from a total of 10 MS patients classified as RR-MS patients, 10 SP-MS patients, and eight sex- and age-matched healthy controls (HC) in the Department of Neurology at the Donostia University Hospital. All donors provided written informed consent prior to sample extraction. The main clinical and demographical characteristics of both patients and healthy donors are summarised in g for 20 min to separate the plasma from the cellular fraction. Plasma was carefully collected, aliquoted and stored at −80 °C.Peripheral blood was collected by venipuncture in EDTA tubes  and centrifuged at 1258× g for 2 min, supernatant was transferred to a new tube and centrifuged again at 20,000× g for 20 min to pellet EVs. The pellet was then resuspended with 100 µL of DPBS . The DPBS had previously been double-filtered through a 0.22 µm-pore filter in order to remove particles and aggregates. RNA was directly isolated from the EV samples by using Trizol LS  following the manufacturer’s protocol. RNA was quantified by NanoDrop ND-1000 spectrophotometer .EVs were isolated following a differential centrifugation step protocol as previously described by our group . BrieflyThe size distribution and concentration of isolated plasma EVs were measured using a NanoSight LM10 device , as described elsewhere . SamplesFor visualization of the isolated EVs, samples were vitrified following standard protocols . Glow-diFor library preparation and sequencing, a minimum input of 2 µg RNA was required. In order to fulfil this criterium, RNA concentration was measured by Nanodrop ND-1000 spectrophotometer  and samples were pooled in pairs or trios of samples with the same disease status and sex. A total of 12 pools were obtained, 4 RR-MS pools, 4 SP-MS pools and 4 HC pools. 6 reads were obtained per sample. All the steps explained above are schematically shown in The concentration and quality of the RNA pools was measured using Bioanalyzer 2100 instrument  before library preparation at CD Genomics . After normalization, rRNA was depleted from the total RNA sample using the Ribo-Zero rRNA removal kit  and followed by purification and fragmentation steps. To construct the sequencing libraries, a strand-specific cDNA synthesis was performed, the 3′ ends were adenylated, and adaptors were ligated. The resulting libraries were subjected to standard quality control and normalization processes. Paired-end sequencing was performed with Illumina HiSeq X Ten , and an average of 40–50 × 10Sequencing reads were quality checked and mapped to the hg19 using BWA  or Bowtip-value less than 0.05 (p < 0.05) were considered differentially expressed circRNAs . CircRNAs detected in at least one pool for a given group and absent in all the pools comprising the other group included in the comparison were considered as group-exclusive circRNAs.CircRNAs detected in at least one pool for each of the groups compared, with an absolute fold-change (FC) value higher than 1.5 (FC > |1.5|) and a p-value < 0.05. Linear RNAs detected in at least one pool for a given group and absent in all the pools comprising the other group included in the comparison were considered as group-exclusive transcripts.After the quality check, the sequencing reads were mapped to the hg19 with STAR  using deCircRNAs were defined as those detected with at least two reads by CIRI2 and find_circ. For linear transcripts, gene type information was obtained from the Biomart database. For transcripts that were not classified in Biomart, gene type information was manually completed based on GeneCards, Ensembl and Lncipedia. Twelve transcript type categories were finally defined: protein coding transcript, long noncoding RNA (lncRNA), pre-microRNA (pre-miRNA), miscellaneous RNA (such as RNAs involved in important ribonucleoprotein complexes implicated in the transcription and translation processes), small nuclear RNA (snRNA), small nucleolar RNA (snoRNA), small Cajal body-specific RNA (scaRNA), ribosomic RNA (rRNA), transfer RNA (tRNA), circRNA, other RNAs  and nondefined RNAs.For each transcript type, the mean number of reads was calculated for each condition  by calculating the mean for the raw read count of the samples comprising each group. Statistical difference between distributions was calculated by chi-squared test, performed using R studio.Dudekula et al. defined circRNAs with more than 20 miRNA binding sites (BS) as “super-sponges” for miRNAs . Thus, tThe sequence of an RNA molecule is usually not sufficient for a reliable structure prediction. However, its combination with experimental structure data obtained from methods based on the study of structure-specific chemical modifications such as the SHAPE-MaP  method uThe CircRNA sequences was obtained from CircInteractome. The sequence was folded in silico using the RNAfold function from Vienna package 2.0. to calculate the minimum thermodynamic free energy, and later normalized with the spliced length of the circRNA to calculate the −∆G/nt value. Based on this value, circRNAs were classified as highly structured (−∆G/nt > 0.25) or poorly structured (−∆G/nt < 0.2). Statistical difference between distributions was calculated by chi-squared test, performed using R studio.p-value < 0.05 and FC > |1.5|.Gene ontology analysis has been performed by ShinyGO v0.741   using thNTA results show a particle size distribution that confirms efficient isolation of small EVs and removal of larger particles such as plasma platelets, with most vesicles ranging between 50 and 300 nm A. MoreovFor the RNA profiling of EVs from MS patients and HC, we performed an RNA-seq of rRNA-depleted total RNA from plasma-derived EVs of 20 MS patients and eight HCs divided into four RR-MS pools, four SP-MS pools and four HC pools. Find_circ and CIRI2 detected a total of 10,906 and 17,542 unique circRNAs supported by at least two BSJ spanning reads, respectively. A good detection overlap was observed between both algorithms, with 6575 circRNAs in common, which were classified as bona fide circRNAs. The linear transcriptome profile of EVs was also studied, and linear RNAs from 18,372 different genes were detected using HTSeq.Most of the circular and linear transcripts were modestly expressed, with 60.7% of the circRNAs and 65.6% of the linear RNAs detected with a mean of less than 10 reads per sample. Among the rest of the transcripts with a Base Mean ≥ 10 reads/sample, it is worth noting that 3214 linear transcripts (17.5%) were detected with a mean of more than 50 reads/sample, out of which 763 (4.1%) are highly abundant transcripts, accounting for more than 500 reads/sample. Among the circRNAs, highly abundant circRNAs have also been detected, although their proportion is smaller. A total of 819 circRNAs (12.5%) were detected, with an average of more than 50 reads per sample, and among those was a small group of 72 circRNAs (1.1%) that stands out as highly abundant (Base Mean ≥ 500 reads/sample) A.Nevertheless, it is worth noting that linear transcripts were quantified at gene level while circRNAs were not. Out of the 6575 bona fide circRNAs detected, 206 circRNAs are intergenic and have not been assigned to any host-gene, and the remaining 6369 are located in a known gene locus. However, only 2814 different host-genes were identified, revealing that some genes produce more than one circular transcript. In fact, 54.1% of those genes give raise a single detectable circRNA transcript, while 44.3% produce between 2 and 10 circRNAs. There is a small subset of genes (1.5%) from which more than 10 different circRNAs are generated and incorporated into EVs, with a maximum of 31 circRNAs produced from the gene coding for the serine/threonine-protein kinase TAO1 (TAOK1) B.Taking together all the linear and circular transcripts, we have analysed more than seven million reads over 15,000 different transcripts per sample pool. In order to characterize the complete transcriptome in EVs, we categorized those transcripts into 12 different types, as defined in the materials and methods section. All 12 transcript types were present in all the samples, but different distributions have been observed. Obtained data show that protein-coding transcripts are the most prevalent in plasma-derived EVs, accounting for more than 92.9% of the total reads per sample. Interestingly, among the rest of non-protein coding RNAs , circRNAp < 0.0001). In leukocytes, miscellaneous RNAs are the ones that are more abundant among the non-protein-coding transcripts (56.2%), a surprisingly high proportion that is not reflected in EVs, where they only account for 1.9% of the reads (p < 0.0001) . In both cases, protein-coding transcripts are the most prevalent, but they represent a smaller proportion in leukocytes . Regarding the ncRNA part, in contrast with what we found for EVs, circRNAs only account for 0.9% of the reads (compared with 58.4% in EVs) ( 0.0001) B.With the hypothesis that patients diagnosed with RR-MS and SP-MS could present a different EV transcriptomic profile, we performed three different comparisons: RR-MS vs. HC, SP-MS vs. HC and SP-MS vs. RR-MS.p-value < 0.05), with 47 of them upregulated (seven upregulated circRNAs with p-adj < 0.05) and 53 downregulated in RR-MS patients (four downregulated circRNAs with p-adj < 0.05)  were exclusively detected in RR-MS samples, whereas 1413 circRNAs (23.2%) were exclusive to HCs A. Furthe < 0.05) A.p-adj < 0.05) in SP-MS patients and 43 downregulated (one downregulated circRNAs with p-adj < 0.05) , were only detected in HCs, while the SP-MS-specific profile included 766 circRNAs (15%) B. From t < 0.05) B.p-adj < 0.05), and 54 downregulated (six downregulated circRNAs with p-adj < 0.05)  in common between both MS types, although the expression of some of them is changed between both group. In fact, 36 circRNAs were found to be significantly upregulated in SP-MS patients (four upregulated circRNAs with  < 0.05) C. Moreov < 0.05) C. Table In the same way that the circular transcriptome is different when we compared EVs from RR-MS, SP-MS and HC individuals, the linear transcriptome was also found to be different.p-adj < 0.05), and only 46 were found to be upregulated in RR-MS patients (two upregulated linear RNAs with p-adj < 0.05)  as there are in the RR-MS group (3169) A. Additi < 0.05) A.p-adj < 0.05) in SP-MS patients and 192 downregulated (20 downregulated linear RNAs with p-adj < 0.05)  in SP-MS vs. 7629 transcripts (49.3%) in HCs). For the linear RNAs detected in both groups (6481 transcripts), 136 transcripts are found to be upregulated (22 upregulated linear RNAs with  < 0.05) B.p-adj < 0.05) and 92 downregulated linear transcripts in SP-MS patients (10 downregulated linear RNAs with p-adj < 0.05)  and 1756 linear transcripts (13.6%) can only be found in EVs from SP-MS patients C. Moreov < 0.05) C. Gene oThe miRNA-sponging function is one of the most studied circRNA functions. However, it has been proposed that, to efficiently inhibit the function of a specific miRNA, a high number of binding sites (BS) for the target miRNA should be present in each circRNA molecule ,21. In op < 0.0001). In order to understand whether circRNAs in EVs are unusually short, we included circRNAs detected in the leukocyte dataset previously published by our group [p < 0.0001). Moreover, circRNAs detected in leukocytes are longer than those found in EVs  but still much shorter than the “super sponge” circRNAs and the overall circRNAs included in circBase (p < 0.0001)  than the circRNAs in our EVs samples  ( 0.0001) .p = 2.2 × 10−16), indicating that the number of miRNA BS proportionally increases with the length of the circRNA   A.p < 0.0001) , while poorly structured circRNAs are more frequent in EVs (18.7% PS circRNAs in leukocytes vs. 29.9% in EVs) ( 0.0001) B.The EV transcriptome profile in MS was characterized back in 2017 by Selmaj et al., where they used RNASeq to study the expression of several classes of transcripts including small RNAs, and with a particular interest in miRNAs. This study revealed that exosomes, or small EVs, have a distinct RNA profile in RR-MS patients, and suggested that miRNAs might be a biomarkers for relapses . NeverthIn this study, we present a genome-wide characterization of the transcriptome in EVs, including for the first time the circular transcriptome. We did not create a particular library preparation to specifically sequence small RNAs, but we still could detect some pre-miRNAs and snoRNAs . Despite the technical differences between studies, we confirmed that protein-coding genes comprise the most prevalent type of transcripts in EVs, while pre-miRNAs are quite scarce . In contrast, we found that circRNAs are abundant in EVs, which is in line with what has been found in other studies ,19. IndePrevious studies on EV RNA content have reported that cell transcriptomes are only partially reflected in EV RNA cargo ,57, whicIn our study, we have found differences in the RNA biotypes between leukocytes and EVs. Remarkably, circRNAs are overrepresented in EVs  compared to leukocytes  . In ordeAmong these factors, high abundance is thought to favour the incorporation of a given RNA type into EVs . In our Interestingly, highly structured circRNAs have been described to be able to regulate the innate immune response in Systemic Lupus Erythematosus patients by binding and inhibiting the activation of the PKR . TherefoBesides intrinsic features of circRNAs which could favour or hinder their incorporation into EVs, the state of cells also impacts EV RNA profiles, and a given RNA could be preferentially packaged or not due to its physiological or pathological implications. In this line, beyond characterizing the general transcriptome profile of EVs in comparison to that from leukocytes, we have also characterized the differences between EVs from healthy donors and MS patients. In agreement with what Selmaj et al. previously reported , we haveAnyway, both circular and linear transcripts differentially expressed between MS patients and healthy controls as well as transcripts that are unique to the diseased conditions could potentially be used as minimally invasive biomarkers of the disease. In fact, it is worth noting that one of the circRNAs found to be altered in RR-MS patients’ EVs when compared to controls’ EVs (circNEIL3) has previously been suggested as a biomarker candidate in leukocytes from RR-MS patients . In contTo the best of our knowledge, this study is the first to report the presence of 6575 circRNAs in plasma-derived EVs from MS and HC individuals. Based on the results drawn from the comparison of the transcriptomic profile between EVs and leukocytes, we suggest that the loading of circRNAs into EVs is a regulated process. Thus, the selective release of circRNAs into EVs could be implicated in the regulation of the physiopathology of the disease, although further research is needed.Moreover, we report a number of linear and circular RNAs that are differentially expressed between MS and healthy controls or between RR-MS and SP-MS patients, which should be further studied in order to evaluate their potential role as biomarkers of MS.


Staphylococcus aureus and Escherichia coli, the antifungal activity of CKR12 was lower than that of FK13. CKR12-PLGA showed higher antibacterial activities against S. aureus and E. coli and higher antifungal activity against Candida albicans compared to those of FK13. Additionally, CKR12-PLGA showed no hemolytic activity in erythrocytes, and scanning and transmission electron microscopy suggested that CKR12-PLGA killed and disrupted the surface structure of microbial cells. Conjugation of antimicrobial peptide fragment analogues was a successful approach for obtaining increased microbial activity with minimized cytotoxicity.Various peptides and their derivatives have been reported to exhibit antimicrobial activities. Although these activities have been examined against microorganisms, novel methods have recently emerged for conjugation of the biomaterials to improve their activities. Here, we prepared CKR12-PLGA, in which CKR12  was conjugated with poly (lactic-co-glycolic) acid (PLGA), and compared the antimicrobial and antifungal activities of the conjugated peptide with those of FK13  and CKR12 alone. The prepared CKR12-PLGA was characterized by dynamic light scattering and measurement of the zeta potential, critical micellar concentration, and antimicrobial activities of the fragments and conjugate. Although CKR12 showed higher antibacterial activities than FK13 against  Antimicrobial peptides (AMPs), as host defense peptides, show potential as new therapeutic classes of antimicrobials . These pDerivatization of AMPs is a particularly successful approach for increasing antimicrobial activity. A hybrid peptide designed by combining the α-helix fragment with the core antimicrobial cationic fragment was reported to have higher antibacterial activity than either fragment alone . The netLL-37, an amphipathic α-helical peptide isolated from humans and belonging to the cathelicidin family , is a caPoly (lactic-co-glycolic) acid (PLGA) has been used as a high-hydrophobic biomaterial because of its biodegradability and potential to control the timing of drug release from nanoparticles ,15. HoweStaphylococcus aureus, Escherichia coli, and Candida albicans. This conjugate may be applied to deliver antibacterial drugs based on its ability to self-assemble into a micellar structure.In this work, we evaluated the mechanism of an AMP-PLGA conjugate and attempted to enhance its antimicrobial activity. We focused on FK13, a fragment of LL-37, and its mutant, CKR12. Moreover, CKR12 was conjugated with PLGA as CKR12-PLGA, and the conjugate and fragments were evaluated to determine their antimicrobial activity against We first evaluated the structural properties of the peptides. The prediction suggested that the fragments FK13 and CKR12 had higher helical contents (84.6%) compared to LL-37 (78.4%). The molecular properties were also calculated, and the values are summarized along with the helical contents in As shown in Subsequently, the designed peptide CKR12 was prepared and conjugated with PLGA. Conjugation was performed according to a previous report  with sli1H-nuclear magnetic resonance (NMR) spectroscopy was also performed for PLGA and the conjugate. The chemical shifts of the signals assigned to PLGA were indistinguishable among the spectra. The FT-IR and NMR results indicate that the prepared CKR12-PLGA contained PLGA as either a conjugation or mixture.To confirm that conjugation was successful, we measured the Fourier transform infrared (FT-IR) spectra of PLGA and CKR12-PLGA. Both spectra showed comparable bands corresponding to the -OH and -COOH groups of PLGA. To clarify whether CKR12 and PLGA were conjugated, we measured the critical micelle concentration (CMC), dynamic light scattering (DLS) spectra, and zeta potential of the prepared CKR12-PLGA .The relative intensities of scattered light were monitored and traced as the mean diameter of the polymeric conjugate, which was found to be 217.3 ± 30.4 nm and showed monophasic aspects A. The zeAfter confirming the conjugation of CKR12 and PLGA, we examined the antibacterial activities of the fragments and conjugate using the micro-broth dilution method .p-value; however, this value could not be determined for S. aureus because of the statistical dispersion of the results. First, the MIC values for FK13 were determined as 14.1 µM for S. aureus and E. coli, and 28.1 µM for C. albicans. Comparison of the MIC values for FK13 and CKR12-PLGA showed that all three microorganisms, S. aureus, E. coli, and C. albicans, were more susceptible to CKR12-PLGA than to FK13 . For example, C. albicans showed 24.2 µM for the conjugate, and the value was slightly lower than that of FK13 (28.1 µM). Two microorganisms, S. aureus and E. coli, were more susceptible to CKR12 than to CKR12-PLGA . The effects of PLGA alone was examined and confirmed showing minimal antimicrobial activity against the three studied microorganisms. Moreover, no hemolytic activity was observed even at the highest concentration (232 µM) of CKR12-PLGA (data not shown).The MIC values in each microorganism were statistically evaluated to estimate the S. aureus, E. coli, and C. albicans. As shown in We next monitored whether CKR12-PLGA affected the morphology of Staphylococcus aureus was monitored by SEM, as shown in E. coli  and presence (right panel) of CKR12-PLGA (We next performed transmission electron microscopy (TEM) of R12-PLGA .S. aureus showed no morphological changes after treatment with CKR12-PLGA, and the results were similar to those observed by SEM, although a crack was observed in the inner part of the cell  and lower antifungal activity against C. albicans (MIC > CMC) compared to those of FK13. AMPs rapidly neutralize a broad range of microbes, including both gram-positive and gram-negative bacteria, mainly by binding to and perturbing the cell envelopes containing lipoteichoic acid and lipopolysaccharide, respectively, as well as their cytoplasmic membranes [S. aureus and E. coli. The surface charge of C. albicans has a zeta potential of approximately −20 to −35 mV, which is less than that of the former two bacteria, and shows high lipophilicity [C. albicans, suggesting that the self-assembled micelle of CKR12-PLGA can attack the bacterial cell membrane of C. albicans, as shown in Comparison of the antibacterial activities of FK13, CKR12, and CKR12-PLGA and MIC of CKR12 revealed lower antibacterial activity against embranes ,24. In fembranes . Each MIhilicity  despite hilicity . The MICS. aureus differed from those of E. coli and C. albicans. Previous reports suggested that the antimicrobial effects of AMPs are conferred by their α-helical structures, which can form pores in the membrane [S. aureus, and that CKR12-PLGA was less effective for deforming the cell surface structure of S. aureus but still gave a certain warp by forming pores. Thus, the antimicrobial properties of CKR12-PLGA observed by electron microscopy agreed with the measured antimicrobial activities.Deformation of the microorganisms was observed in the presence of CKR12-PLGA; however, the morphological changes of membrane ,27. Our S. aureus and E. coli and those of a mutant conjugated with PLGA (CKR12-PLGA) against S. aureus, E. coli, and C. albicans were evaluated. Conjugation of the AMP fragment analogues and biopolymers was a successful approach for obtaining increased antimicrobial activity and achieving a broad antibacterial spectrum with no hemolytic activity, although the mechanism has not been fully clarified yet. Further studies are needed to improve the formation of the micellar structure of AMP analog conjugates with PLGA, which will be a useful tool for delivering antimicrobial drugs.In this study, the antimicrobial activities of the LL-37 fragment mutant (CKR12) against d,l-lactic-co-glycolic acid) , 3-(2-pyridyldithio) propionylhydrazide (PDPH), N,N′-dicyclohexylcarbodiimide, N-hydroxysuccinimide, and Sudan III were purchased from Wako Pure Chemical Industries .The LL-37 fragment (17–29) was purchased from Funakoshi Co., Ltd. . The mutant peptide (CKRIVKRIVKKWLR) was synthesized by the Toray Research Center . Poly (S. aureus (NRBC 12732), E. coli (NRBC 3972), and C. albicans (JCM 1542).Three microbial strains were purchased from the Biological Resource Center, National Institute of Technology and Evaluation (NBRC)  and Japan Collection of Microorganisms in Riken BioResource Research Center . The strains used in this study were http://aps.unmc.edu/AP/main.php, accessed date: 10 September 2020) and NetSurfP-2.0 [The primary structure characteristics (including net charge and hydrophobic residues) of LL-37, LL-37 fragment (17–29) and the mutant peptide were predicted using the Antimicrobial Peptide Database  at a frequency of 500 MHz. FT-IR can be used to analyze and compare changes in polymer binding to drugs and characterize protein structures. The infrared absorption spectra of the PLGA conjugate and PLGA were measured in CHCl3 with an IRAffinity-1 . Both spectra were recorded at room temperature.The CMC is defined as the lowest concentration of surfactant at which micelles form in water. The CMC was determined from the absorbance of Sudan III at the maximum absorption wavelength (511 nm) by the dye solubilization method using a spectrophotometer .The sizes and surface charges of PLGA-conjugated micelles were measured using a DLS instrument . PLGA-conjugated micelles were dissolved in distilled water. The effective hydrodynamic diameters and zeta potentials of the PLGA-conjugated micelles were measured in triplicate.v/v) Triton X-100  were used as negative and positive controls, respectively.The CKR12-PLGA concentrations (from 0.06 to 232 µM) at which hemolysis of sheep erythrocytes occurred was measured at 540 nm. Sheep erythrocytes in 10 mM phosphate-buffered saline (PBS)/10% (S. aureus and E. coli) in the exponential growth phase were diluted to a concentration of 4 × 104 CFU/mL with Mueller-Hinton broth and then diluted to 4 × 104 CFU/mL with YM broth; 180 µL of the culture was dispensed into each well of a 96-well microtiter plate. Susceptibility tests were performed using two-fold standard broth microdilutions of FK13, CKR12, and CKR12-PLGA according to Clinical and Laboratory Standards Institute guidelines. MICs were measured using test samples from 232 to 0.06 µM. Each analysis was performed in triplicate. The lowest concentration (highest dilution) required to prevent the growth of microorganisms was regarded as the MIC.The antibacterial activity of the peptides was characterized by determining their MICs. Bacterial strains (Escherichia coli and S. aureus cell suspensions (1 × 108 CFU/mL) were incubated with CKR12-PLGA (61 µM) at 37 °C with shaking at 180 rpm. Candida albicans cell suspensions (1 × 108 CFU/mL) were incubated with CKR12-PLGA (61 µM) at 27 °C. Two milliliters of the mixture were collected at 2 h and centrifuged at 1000× g for 5 min, and the supernatant was discarded. The bacterial cells were washed with PBS three times, fixed with 2.5% glutaraldehyde at 4 °C overnight, washed twice with PBS again, and postfixed for 2 h with 1% OsO4. The prepared bacterial pellets were dehydrated with a graded series of ethanol, following which the dried cells were coated with gold and observed using a scanning electron microscope . The prepared pellets were observed using a transmission electron microscope  for imaging.For microscopic measurements, the three microorganisms were prepared as follows. ®. Statistically significant effects were further analyzed, and means were compared by the Tukey-Kramer test. Statistical significance was set at p < 0.05.Experimental data were analyzed by one-way analysis of variance using the general linear model procedure of BellCurve for Excel


Methods: We performed a manufacturer-independent, cross-sectional, diagnostic accuracy study involving two Italian hospitals. Sensitivity, specificity, positive (PLR) and negative likelihood ratio (NLR), positive (PPV) and negative predictive value (NPV) and diagnostic accuracy with 95% confidence intervals (95% CI) of Inflammacheck® were calculated using the RT-PCR results as the standard. Further RT-PCR tests were conducted on NP specimens from test positive subjects to obtain the Ct (cycle threshold) values as indicative evidence of the viral load. Results: A total of 105 individuals  were included in the final analysis, with the RT-PCR being positive in 13 (12.4%) and negative in 92 (87.6%). The agreement between the two methods was 98.1%, with a Cohen’s κ score of 0.91 (95% CI: 0.79–1.00). The overall sensitivity and specificity of the Inflammacheck® were 92.3% (95% CI: 64.0%–99.8%) and 98.9% (95% CI: 94.1%–100%), respectively, with a PLR of 84.9 (95% CI: 12.0–600.3) and a NLR of 0.08 (95% CI: 0.01–0.51). Considering a 12.4% disease prevalence in the study cohort, the PPV was 92.3% (95% CI: 62.9%–98.8%) and the NPV was 98.9% (95% CI: 93.3%–99.8%), with an overall accuracy of 98.1% (95% CI: 93.3%–99.8%). The Fagan’s nomogram substantially confirmed the clinical applicability of the test in a realistic scenario with a pre-test probability set at 4%. Ct values obtained for the positive test subjects by means of the RT-PCR were normally distributed between 26 and 38 cycles, corresponding to viral loads from light (38 cycles) to high (26 cycles). The single false negative record had a Ct value of 33, which was close to the mean of the cohort (32.5 cycles). Conclusions: The modified Inflammacheck® device may be a rapid, non-demanding and cost-effective method for SARS-CoV-2 detection. This device may be used for routine practice in different healthcare settings .Background: The standard test that identifies the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is based on reverse transcriptase-polymerase chain reaction (RT-PCR) from nasopharyngeal (NP) swab specimens. We compared the accuracy of a rapid antigen detection test using exhaled breath condensate by a modified Inflammacheck The new severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) first appeared in December 2019, and it subsequently spread rapidly worldwide causing a global pandemic [Before SARS-CoV-2 infection manifests itself, there is usually an incubation period lasting up to 14 days, with a median of approximately 5 days from exposure to symptom onset . The earCurrently, the reference standard test accepted for identification of SARS-CoV-2 positive subjects is based on molecular assays detecting viral RNA by reverse transcriptase-polymerase chain reaction (RT-PCR) from nasopharyngeal (NP) swabs . Most di® device is a novel, hand-held, fully automated in vitro diagnostic medical device for non-invasive detection of SARS-CoV-2 in exhaled breath at point of care. It integrates the safe collection of EBC with an automated platform for SARS-CoV-2 detection through an embedded electrochemical sensor. The sensor surface is coated with a macromolecule to which the virus binds, producing a measurable signal indicating whether SARS-CoV-2 is present or not. The test assay renders a result after less than 6 min. EBC is collected by the Inflammacheck® device through normal breathing, making this investigation non-invasive, rapid, reliable and easy to perform. The aim of our study was to compare the diagnostic sensitivity and specificity of the Inflammacheck® device for SARS-CoV-2 detection with the standard RT-PCR of NP swab specimens.SARS-CoV-2 may spread via small droplets in breath and aerosols  and therWe carried out a cross-sectional multicentre study across two independent hospitals of Campania Region in Italy, namely Pulmonary Rehabilitation Unit of Istituti Clinici Scientifici Maugeri Spa SB, IRCCS of Telese Terme, Benevento, and Boscotrecase Hospital, Boscotrecase, Naples. We enrolled four groups of patients at different stages of the diagnostic/screening process for potential SARS-CoV-2 infection: group 1, subjects with clinically suspected COVID-19; group 2, convalescent COVID-19 patients undergoing pulmonary rehabilitation for persistent pulmonary and/or functional limitations within four weeks from acute hospital discharge; group 3, asymptomatic subjects with a high probability of SARS-CoV-2 infection; group 4, asymptomatic subjects with a low probability of SARS-CoV-2 infection. The level of clinical suspect was established by physicians, based on the presence/absence of typical COVID-19 symptoms  and of compatible radiological findings on chest X-ray or chest computed tomography (CT) scans. The major inclusion criteria were age ≥ 18 years and informed consent signature. Exclusion criteria were: invasive or non-invasive ventilation, high-flow oxygen, symptomatic hypoxia or oxygen saturation ≤ 92% (≤88% in chronic obstructive pulmonary disease) despite oxygen supplementation at 4L/min via nasal cannula, suspicion of alcohol or drug abuse or any other condition associated with poor compliance in the investigator’s opinion. The study was approved by the Institutional Review Board of Istituto Nazionale Tumori, Fondazione Pascale, Naples, Italy with reference number 2/21. All patients provided written informed consent.™ chemistry) using fluorogenic oligonucleotide probe molecules specific to the amplicons of their respective targets. TaqMan™ probes are designed such that they anneal within a DNA region amplified by a specific set of primers. The Nsp2 region is detected by means a TaqMan™ probe labeled with a FAM fluorophore (470/510 nm) while the N gene is detected by using a TaqMan™ probe labeled with a HEX fluorophore (530/555 nm). A TaqMan™ probe labeled with a Far-Red fluorophore (680/715 nm) is used for SPC2 detection. When amplification is complete, the NeuMoDx™ System software analyzes the data and expresses the result as positive if one or both target genes have been detected, and as negative if both target genes are not amplified while SPC2 is, as undetermined in the case of an instrumental error or, finally, as unresolved in the case of the instrument’s inability to express a valid result. Quantification of the viral RNA load was achieved by employing the comparative threshold cycle (Ct) method. Ct is defined as the PCR cycle at which the accumulated amount of PCR product achieves an arbitrary threshold. This method allows for precise determination of the viral RNA load in a sample, relative to that of a positive control with known viral RNA load by comparing the Ct of the sample and the positive control included in the PCR assay kit.RT-PCR was performed as the reference standard on the same day of the index test using the NeuMoDx™ 300800 , with results inferred according to the manufacturer’s specifications. The NeuMoDx™ SARS-CoV-2 assay is an automated sample-to-answer assay that received emergency use authorization from the FDA. It is a multiplex assay targeting two regions of the viral genome, namely Nsp2 and the N genes. The NeuMoDx™ System automatically performs all the steps required to extract the target nucleic acid and prepare the isolated RNA for RT-PCR and, if present, amplifies and detects target sequences of the Nsp2 N genes. The NeuMoDx™ System uses a combination of heat, lytic enzyme and extraction reagents to automatically perform lysis, RNA extraction and removal of inhibitors using the separately available NeuMoDx™ reagents. The released nucleic acids are captured by paramagnetic particles. The particles, with bound nucleic acid, are loaded into the “NeuMoDx™ Cartridge where the unbound elements are washed away with NeuMoDx™ Wash Reagent”. The bound RNA is then eluted using NeuMoDx™ Release Reagent. The NeuMoDx™ System uses the eluted RNA to rehydrate proprietary NeuDry™ amplification RT-PCR mix containing all the elements necessary for amplification of both SARS-CoV-2 and sample process control (SPC2) targets. The amplified targets are detected in real time using hydrolysis probe chemistry . The breath collection unit is sealed off towards the rest of the Inflammacheck® system to mitigate the risk of cross-infection. It is composed of a sensor cartridge with a built-in single-use sensor, a valve house directing the airflow through the system and a bacterial viral filter. The filter serves to filter ambient air before it is inhaled, as well as to filter exhaled breath before it leaves the breath collection unit. To perform a test, the Inflammacheck® is switched on, and the breath collection unit is inserted. It has an embedded RFID tag containing information on the sensor and sensor cartridge, including manufacturing batch and dates, which is read by the device and stored along with the test data establishing traceability in the system. The device performs a self-check to ensure the system is fully functional and capable of performing a test, and then initiates cooling by means of a Peltier element to bring down the temperature at the condensation area to below 6 °C. When this temperature has been reached, the device emits a beep and tells the subject to start breathing through the mouthpiece of the breath collection unit. When exhaling, the subject breathes onto a condensation area, which is part of the sensor cartridge, to form a test sample of EBC. During sample collection, EBC builds up in the condensation area until enough has been collected . Then it automatically flows into a sensor capillary. The device monitors the fill of the sensor capillary to ensure an adequate amount of sample is present to perform a test. Upon registered fill, the device emits a beep and instructs the subject to stop collecting the sample and place the device on a table. The device automatically proceeds into the analytical assay. The device performs a first test scan to establish a baseline pre-curve, and then proceeds into a 5 min incubation period where the virus, if present in the EBC, binds to the macromolecule coated sensor surface. After incubation, a second test scan is performed to build a post-curve. The presence of virus is determined by comparing pre- and post-curves. Less than 6 min after fill detection, the test result is presented back to the operator/test subject via the built-in display on the device  and negative likelihood ratio (NLR), positive (PPV) and negative predictive value (NPV) and diagnostic accuracy with 95% confidence intervals (95% CI) of Inflammacheck κ score . DiagnosOf 119 patients screened for eligibility, six (5.0%) were ineligible for protocol adherence issues. Four (3.4%) refused to participate in the study. A total of four (3.7%) out of the 109 eligible patients were not considered because measurement failed due to technical problems. Thus, 66 participants from Istituti Clninci Scientifici Maugeri and 39 from Boscotrecase Covid Hospital entered the study. Overall, a total of 105 individuals  were included in the final analysis, of which 21 (20.0%) were subjects with clinically suspected COVID-19 (group 1), 20 (19.0%) convalescent COVID-19 patients (group 2), 14 (13.3%) were asymptomatic participants with a high clinical probability of SARS-CoV-2 infection (group 3) and 50 (47.6%) were asymptomatic participants with a low clinical probability of SARS-CoV-2 infection (group 4) .® device. A further discrepancy was a 31-year-old woman who tested a false positive on Inflammacheck®. Thus, similarly to RT-PCR, the test performed with the Inflammacheck® device was positive in 13 (12.4%) cases and negative in 92 (87.6%) cases in our study sample  and negative in 92 (87.6%). One 57-year-old male participant tested positive with RT-PCR but negative with the Inflammachecky sample .We also extracted and recorded Ct values from the NeuMoDx™ System  obtained® were 92.3% (95% CI: 64.0%–99.8%) and 98.9% (95% CI: 94.1%–100%), respectively, with a PLR of 84.9 (95% CI: 12.0–600.3) and an NLR of 0.08 (95% CI: 0.01–0.51). Considering a 12.4% disease prevalence in the study cohort, the PPV was 92.3% (95% CI: 62.9%–98.8%) and the NPV was 98.9% (95% CI: 93.3%–99.8%), with a diagnostic accuracy of 98.1% (95% CI: 93.3%–99.8%). Since PPV, NPV and diagnostic accuracy can vary depending on prevalence data, these three indicators were also estimated in a realistic scenario reflecting the SARS-CoV-2 positivity rate in Italy at the time of the examination. Thus, with an estimated 4% disease prevalence, the PPV and the NPV were 78.0% (95% CI: 33.4%–96.2%) and 99.6% (95% CI: 97.9%–99.9%), respectively, with an overall accuracy of 98.6% (95% CI: 94.1%–99.9%). Accordingly, based on likelihood ratios and the pre-test probability set at 4%, the Fagan’s nomogram confirmed that the post-test probability increased to 78% if the patient tested positive and decreased to 0.4% in case of a negative result with the Inflammacheck® device . The overall sensitivity and specificity of the Inflammacheck® device .® device, as compared to NeuMoDx™ System RT-PCR NP swab, identifies SARS-CoV-2 in EBC excellently, with sensitivity and specificity of 92.3% and 98.9%, respectively. Moreover, the analysis of the likelihood ratios and the Fagan’s nomogram suggest that the test could be considered suitable for routine practice. Results of our preliminary study suggest that the modified Inflammacheck® permits a non-invasive detection of SARS-CoV-2 with high sensitivity and specificity in less than 6 min. In addition, EBC collection does not require manipulation of the sample as it is collected by the device itself through normal breathing, making this investigation non-invasive, rapid, reliable and easy to perform. Collecting EBC specimens has several advantages over NP swabs, among which are a lower risk of viral spread and/or environmental contamination and, above all, minimal training is required and the method can be carried out by anyone. In addition, EBC sampling can repeatedly be performed as many times as needed in follow-up investigations. Thanks to the social measures implemented and the availability of effective vaccines, the pandemic epidemiological curve has progressively improved. However, the abolition of social restrictions, together with the resumption of international travel as well as the appearance of new viral variants make the rapidity and specificity of diagnostic tests extremely important to identify and isolate in a very short time all infected subjects in the asymptomatic phase.Currently, RT-PCR assay represents the gold standard for diagnosis of SARS-CoV-2 infection and can be performed on nasopharyngeal and oropharyngeal swabs in symptomatic and asymptomatic people. However, RT-PCR analysis is time consuming and requires dedicated laboratory equipment and personnel specifically trained. Up to 54% of COVID-19 patients may test negative on the initial NP swab samples RT-PCR . Such a A major limitation of our study should be addressed. In detail, a diagnostic accuracy study should ideally enroll a random or consecutive sample of eligible patients with the suspected condition to avoid the case-control design and, therefore, a potential bias. Thus, studies enrolling patients with the target condition and a control group without it may overestimate diagnostic accuracy. Moreover, our choice of enrolling four patient groups at different stages of the diagnostic/screening process for potential SARS-CoV-2 infection accounts for the different pre-test probability and, therefore, for the impossibility of performing sensitivity or subgroup analyses other than those related to major demographic variables. Overall, caution is required in interpreting our results, which should be considered preliminary.® enables the qualitative detection of SARS-CoV-2 in EBC samples in a reliable manner, with excellent overall, positive and negative percentage agreements and with a high κ value. Owing to its simplicity and high sensitivity, Inflammacheck® is particularly suited in the triage process and for a rapid screening of a large population, which would be useful at airports, on college campuses, drive-through screening clinics, shopping centres, train stations, point of care facilities, etc. However, the results we presented should be validated in a larger cohort study, and the performance of the device in differentially diagnosing SARS-CoV-2 from similar respiratory viruses should also be checked.Our preliminary results demonstrate that Inflammacheck


The severity of COVID-19 remains high worldwide. Therefore, millions of individuals are likely to suffer from fear of COVID-19 and related mental health factors.The present systematic review and meta-analysis aimed to synthesize empirical evidence to understand fear of COVID-19 and its associations with mental health-related problems during this pandemic period.Relevant studies were searched for on five databases , using relevant terms . All studies were included for analyses irrespective of their methodological quality, and the impact of quality on pooled effect size was examined by subgroup analysis.z = 0.56 for mental health-related factors; 0.54 for anxiety; 0.42 for stress; 0.40 for depression; 0.29 for sleep problems and –0.24 for mental well-being). Methodological quality did not affect these associations.The meta-analysis pooled data from 91 studies comprising 88 320 participants  from 36 countries. The pooled estimated mean of fear of COVID-19 was 13.11 (out of 35), using the Fear of COVID-19 Scale. The associations between fear of COVID-19 and mental health-related factors were mostly moderate (Fisher's Fear of COVID-19 has associations with various mental health-related factors. Therefore, programmes for reducing fear of COVID-19 and improving mental health are needed. Therefore, the uncontrolled pandemic causes several severe problems for individuals globally, and one of these problems relates to mental health.The entire world has experienced the threat of COVID-19 since the initial outbreak in China at the end of 2019. The World Health Organization12 mental health problems  during the COVID-19 pandemic have been high.17 Moreover, one of the primary triggers for mental health problems during this period is fear of COVID-19.18 More specifically, COVID-19 is a new type of infection, and different stakeholders  require information and data to help fight the consequences of the disease. Therefore, fear is likely to develop among many individuals because of the life-threatening effects of COVID-19 and the fact that the many methods implemented to control the infection rate have had varied levels of success. Given that the COVID-19 infection and its severity are unlikely to be under control in the short term,20 it is important to accumulate scientific evidence regarding fear of COVID-19 and its association with mental health-related factors. Using the empirical data regarding the associations between fear of COVID-19 and mental health-related factors, healthcare providers and policy makers can understand the importance of controlling fear of COVID-19 during the pandemic period, and implement initiatives to prevent potential mental health problems.Because the global reach of the COVID-19 pandemic is unprecedented, with many different and vigorous infection control methods (e.g. lockdown) implemented,23 Moreover, sleep has been identified as an important and essential daily activity for individuals to maintain daily functions.24 In this regard, when individuals encounter any problem related to one of these mental health-related factors, their quality of life and well-being is jeopardised, and a minority of individuals may develop serious health problems.27In the present systematic review and meta-analysis, mental health-related factors, including depression, anxiety, stress, sleep problems, mental health-related factors and mental well-being, were identified, analysed and discussed. These factors were included because they are important factors that affect an individual's ability to live a happy and healthy life. For example, depression, anxiety, stress and mental health-related factors have been found to be important factors that jeopardise sleep quality and physical health.27 As a result, society and healthcare system have higher levels of burden if the society and community have larger proportion of residents living with mental health-related problems.27 Therefore, understanding the associations between fear of COVID-19 and the aforementioned mental health-related factors are of great importance during the COVID-19 pandemic period.More specifically, when individuals encounter a mental health-related problem, they need additional support from community and/or healthcare systems to assist them in coping with both mental and physical health problems. Moreover, individuals with mental health-related problems may have decreased productivity, resulting in fewer contributions to society.Consequently, the present systematic review and meta-analysis was carried out to provide empirical evidence for healthcare workers and related stakeholders  to better understand fear of COVID-19 and its associations with mental health-related problems during the pandemic period. The main aims of the review were to (a) estimate the mean fear of COVID-19 scores in the context of the COVID-19 pandemic from studies, using the Fear of COVID-19 Scale (FCV-19S); (b) assess the association of fear of COVID-19 with mental health-related factors  in the context of the COVID-19 pandemic; (c) identify potential sources of heterogeneity and its possible sources for the aforementioned mean and association estimations; and (d) identify moderators in the mean estimation and association between fear of COVID-19 and mental health-related factors.28 The study's findings are reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines.29The project was registered in the International Prospective Register of Systematic Reviews (PROSPERO) website  were systematically searched. COVID-19-related fear, in combination with mental health-related keywords including anxiety, depression, psychological distress, mental well-being and sleep problems, were used to develop search syntax. The relevant search terms were extracted from PubMed Medical Subject Headings and published studies. Search syntax was customised for the aforementioned academic databases based on their search attributes. Additionally, hand searches were performed by reading reference lists of included studies and published systematic reviews to increase the retrieval of relevant studies.30The main outcomes of the present systematic review were mean of fear of COVID-19 was estimated in the context of the COVID-19 pandemic based on FCV-19S scores internationally; and the association of fear of COVID-19 with other mental health-related factors (mentioned below), which was calculated in the context of the COVID-19 pandemic. Moreover, fear of COVID-19 was defined as the threatening stimulus of COVID-19 resulting in the triggering of unpleasant emotional state among individuals.31 anxiety, defined as having excessive worry on various activities, events, topics and daily errand;31 stress, defined as a nonspecific response from an individual's body that reacts to any demands;32 sleep problems, defined as sleep disorders in a broad category with some subcategories, including intrinsic, extrinsic and disturbances of circadian rhythm;33 mental health-related factors, defined as perceived discomfort from response to stressors that is hard to cope with;34 and mental well-being, defined as the psychological processes of individuals that promote life outcomes in a positive way, including happiness and growth toward optimal development.35The secondary outcomes were to identify potential sources of heterogeneity and its possible sources, moderators in mean estimation fear of COVID-19, and moderators in the association of fear of COVID-19 with other mental health-related factors. The other mental health-related factors were defined as follows: depression, defined as lacking interests of engaging in activities and having low mood without pleasure;All peer-reviewed observational studies published in the English language were considered eligible if relevant data regarding mean scores regarding fear of COVID-19 (on the FCV-19S) and their association with mental health problems and/or distress  were reported. To be included, the fear of COVID-19 and mental health-related factors had to have been assessed by valid and reliable psychometric scales. No limitation was exerted regarding participants’ characteristics. More specifically, studies were excluded if they had other study designs , did not report numerical findings regarding the selected outcome measures, did not have valid or reliable measures for assessing the selected variables and were non-English language publications.κ = 0.83).First, titles and abstracts of all retrieved papers were independently screened based on eligibility criteria, by two of the research team. Then full texts of potentially eligible papers were downloaded and reviewed for final selection. During this process, relevant studies were selected. This stage was carried out independently by two members of the research team. The kappa score showed strong agreement between these reviewers .The methodological quality of the included papers was assessed with the Newcastle–Ottawa Scale (NOS) checklist.κ = 0.75).A predefined Microsoft Excel version 2016 for Windows spreadsheet was designed to extract data based on the study aims and selected outcomes. Data extracted included the first author's name, publication date, title of the study, country of research, target population of study , sample size, study design, fear of COVID-19 measures and scores (including mean and s.d.), mental health-related factor outcomes measures and their association with fear of COVID-19, and NOS score . Data extraction of included studies were carried out independently by two members of the research team. The kappa score showed strong agreement between these reviewers : The numerical findings regarding means and standard deviations of fear of COVID-19 scores were reported consistently in 71 included studies. This key measure and its 95% confidence interval were reported.r correlation coefficient was converted to Fisher's z-statistic. Consequently, all analyses were performed with Fisher's z-values as effect sizes.40 Fisher's z-transformation was applied by using the following formula: z = 0.5 × ln[(1 + r) − (1 − r)]. The s.e. of z was calculated based on the following formula: s.e. z = 1/√(n − 3).41 Therefore, the selected measure of effect  is expressed as Fisher's z-score and its 95% confidence interval. Moreover, Fisher's z at 0.1 is defined as weak, 0.11–0.3 is defined as weak to moderate, 0.3 is defined as moderate, 0.31–0.49 is defined as moderate to strong and ≥0.5 is defined as strong. For assessing moderator analysis, subgroup analysis or meta-regression was carried out. Funnel plot and the Begg's test were used to assess publication bias.42 The jackknife method was used for sensitivity analysis43 and to determine the effect of individual studies on the outcome. The jackknife method is also known as the ‘one-out method’, and was used to evaluate the quality and consistency of the results. More specifically, significant changes can be evaluated by removing each study individually.44Correlation of fear of COVID-19 with other mental health-related factors: Other mental health-related factors were defined as depression, anxiety, stress, sleep problems, mental health-related factors and mental well-being. Pearson's correlation coefficient was the selected effect size for meta-analysis in assessing the associations between fear of COVID-19 and these mental health-related factors. Because of the potential instability of variance, Pearson's A quantitative synthesis using Stata software version 14 for Windows was conducted. Meta-analysis was run with random effect model because the included studies were taken from different populations, and both within-study and between-study variances should be accounted for.n = 1768), Web of Science (n = 1200), PubMed (n = 1240), EMBASE (n = 5012) and ProQuest (n = 256). After removing 246 duplicates, 9230 papers were screened based on the title and abstract. Finally, 298 papers deemed as eligible had their full texts were reviewed. During this process, 91 papers met the eligibility criteria and were pooled in the meta-analysis. The initial search of five databases identified 9476 papers: Scopus (n = 10 papers), Iran (n = 6 papers), Bangladesh (n = 5 papers) and Pakistan (n = 5 papers) had the highest number of studies. Almost all studies (n = 90) employed a cross-sectional design. Seven papers collected data during national lockdown periods in their respective countries. The target populations in the studies were either the general population (n = 80) or healthcare professionals (n = 11). Sample size varied between 58 and 10 067 participants. Mean age of participants was 38.88 years. Approximately 61% of the total number of participants were females. The FCV-19S, developed by Ahorsu et al,45 was the most frequently used instrument to assess COVID-19-related fear in 71 studies. Mental health-related factors assessed included sleep problems (n = 9), depression (n = 49), anxiety (n = 48), stress (n = 19), psychological distress (n = 6) and mental well-being (n = 3). Different valid and reliable psychometric instruments were used to assess these outcomes. A total of 91 studies were included in the final analysis. Included studies comprised 88 320 participants from 36 countries . Turkey . More specifically, 76 studies reported mean fear scores, with 71 studies using the FCV-19S and five papers using other instruments. Because of the variation in the number of questions and the scoring method between the FCV-19S and the other instruments, mean estimation of fear of COVID-19 was meta-analysed using the 71 studies that utilised the FCV-19S. The pooled estimated mean of fear of COVID-19 was 13.11 out of 35, according to the FCV-19S  did not consider publication bias, the funnel plot . The funnel plot after trimming is shown in The probability of publication bias was assessed by Begg's test and funnel plot. Although the Begg's test , female-only participants (14.89) and with gender participants 13), but this difference was not significant. Other variables did not influence heterogeneity or estimated pooled mean. Results of the subgroup analysis and meta-regression are shown in , but thiz-score of 0.40 . The forest plots are shown in P = 0.57) or funnel plot . Also, a higher association was observed among studies with male-only participants (0.61) compared with studies with female-only participants (0.32) and both gender participants (0.40), but this difference was not significant. Other variables did not influence heterogeneity or estimated pooled Fisher's z-score. Results of the subgroup analysis and meta-regression are shown in Subgroup analysis showed that association between fear of COVID-19 and depression was significantly higher among healthcare professionals compared with the general population . The forest plots are shown in P = 0.66) or funnel plot , and during the lockdown period compared with not being lockdown (0.70 v. 0.53). Meta-regression showed that age was the only significant moderator in the association of COVID-19-related fear and anxiety, explaining 15.5% variance in this association. Other variables did not influence heterogeneity or estimated pooled Fisher's z-score. Results of the subgroup analysis and meta-regression are shown in Subgroup analysis showed that association between fear of COVID-19 and anxiety was positive and higher, but not significant, among healthcare professionals compared with the general population . The forest plots are shown in P = 0.35), but was found in the funnel plot . The funnel plot after trimming is shown in P = 0.42; The association between fear of COVID-19 and stress was reported in 19 studies. The pooled estimated effect size showed moderate to strong association between fear of COVID-19 and stress, with a Fisher's nel plot . The filv. 0.42 in studies that included both genders) and studies that used FCV-19S to measure fear of COVID-19 , it was not significant. Subgroup analysis showed that association between fear of COVID-19 and stress was significantly higher among healthcare professionals compared with the general population (0.76 v. 0.41). Meta-regression showed that age and methodological quality of studies were the significant moderators in the association of COVID-19-related fear and stress, explaining 11.8% and 15.51 variance, respectively, in this association. Other variables did not influence heterogeneity or estimated pooled Fisher's z-score. Results of the subgroup analysis and meta-regression are shown in Subgroup analysis showed that lowest heterogeneity was observed in studies conducted during lockdown period 35.2%). Although it appears that association between fear of COVID-19 and stress was positive and higher in studies with female-only participants . The forest plots are shown in P = 0.30) or funnel plot . The forest plots are shown in P = 0.26), whereas the funnel plot appeared to be asymmetric . The funnel plot after trimming is shown in P = 0.58; The association between fear of COVID-19 and mental health-related factors was reported in six studies. The pooled estimated effect size showed strong association between fear of COVID-19 and mental health-related factors, with a Fisher's ymmetric . The filv. 0.41 for the general population). Such associations were also higher among studies that used FCV-19S to assess fear of COVID-19 . Meta-regression showed that methodological quality score and instrument used to assess mental health-related factors explained 19.59% and 89.68% variance in this positive association. Other variables did not influence heterogeneity or estimated pooled Fisher's z-score. Results of the subgroup analysis and meta-regression are shown in Subgroup analysis showed that association between fear of COVID-19 and mental health-related factors was significantly higher among healthcare professionals . The forest plots are shown in P = 0.47; z-score. Results of the subgroup analysis and meta-regression are shown in The association of fear of COVID-19 with mental well-being was reported in three studies. The pooled estimated effect size showed negative and weak to moderate association between fear of COVID-19 and mental well-being, with a Fisher's To the best of our knowledge, the present systematic review and meta-analysis is the first to analyse the associations between fear of COVID-19 and a variety of mental health-related factors. More specifically, the systematic review and meta-analysis synthesised the evidence on the associations between fear of COVID-19 and depression, anxiety, stress, sleep problems, mental health-related factors and mental well-being during the COVID-19 pandemic period. After rigorous literature search, full texts of 298 papers were reviewed and 91 studies were included in the meta-analysis. Among the 91 studies, data from 88 320 participants in 36 countries were analysed. Moreover, the present meta-analysis showed that the mean estimation of fear of COVID-19 (using the FCV-19S) was 13.11, which indicates low levels of fear. More specifically, the score range of the fear was between 7 and 35, with a score of <21 indicating a low level of fear. Moreover, no significant gender differences were found in the fear of COVID-19.z = 0.40), and a stronger association was observed among healthcare professionals (0.68) compared with the general population (0.37). The association between fear of COVID-19 and anxiety was strong (Fisher's z = 0.54), and no significant difference in the magnitude of association was found between healthcare professionals (0.67) and the general population (0.53). The association between fear of COVID-19 and stress was moderate to strong (Fisher's z = 0.42), and a stronger association was observed among healthcare professionals (0.76) compared with the general population (0.41). The association between fear of COVID-19 and sleep problems was weak to moderate (Fisher's z = 0.29). The association between fear of COVID-19 and mental health-related factors was strong (Fisher's z = 0.56), and a stronger association was observed among healthcare professionals  The association between fear of COVID-19 and mental well-being was weak to moderate (Fisher's z = −0.27). Meta-regression further showed that country, age, study quality, gender and measures for mental health-related factors were mostly non-significant moderators. Significant moderated effects were identified for age in anxiety and instruments on mental health-related factors . The FCV-19S has been validated in over 20 different languages.144 Therefore, it appears to be the most appropriate instrument assessing fear of COVID-19 for almost all of the studies reviewed in the present systematic review and meta-analysis. Future studies are recommended to use the FCV-19S if they want to assess the phenomenon of fear of COVID-19.The instruments used for assessing fear of COVID-19 and other mental health-related factors are reported in 146) can be designed to tackle fear of COVID-19, and these may subsequently help maintain good mental health among both healthcare professionals and the general population during COVID-19 pandemic. Second, the associations between fear of COVID-19 and other mental health-related factors found in the present systematic review and meta-analysis indicate the importance of addressing the fear of COVID-19 together with other mental health-related factors. This may increase the effects of mental health improvement programmes during the pandemic. However, it should be noted that the present systematic review and meta-analysis found a large I2-value, which indicates the high levels of heterogeneity among the studies evaluated. However, large heterogeneity observed in the present findings is understandable because various factors that can increase the fear of COVID-19 together with the wide range of populations and measures were included in the meta-analysis.According to the findings derived from the present systematic review and meta-analysis, there are a number of implications. First, programmes to reduce fear of COVID-19, especially for healthcare professionals, are recommended during the pandemic period. More specifically, programmes with the support of strong theory  across 36 countries.There are some strengths in the present systematic review and meta-analysis. First, the mean estimation of fear of COVID-19 and its associations with other mental health-related factors were estimated across different countries worldwide. Therefore, the analysis provides a contextualised picture regarding the psychological phenomenon during the COVID-19 pandemic. Second, the methodology of the present systematic review and meta-analysis was rigorous, given that each analysed study had been evaluated for their methodological quality by the NOS checklist. Moreover, a thorough literature review was conducted utilising five academic databases. In addition to the main and secondary outcomes, the synthesised findings were checked for their stability by additional analyses, including subgroup analysis and meta-regression. Third, the present findings have relatively high generalisability because the analysed data come from a large sample size . Therefore, the different item descriptions and scoring method used in these measures may cause biases in estimation. However, meta-regression in the present systematic review and meta-analysis shows that almost all of the measures had no significant effects on the synthesised results. Therefore, this limitation may not be serious. Second, all studies, except for one, that were analysed in the present systematic review and meta-analysis employed a cross-sectional design. Without the time factor in the study design, the associations found in the present findings do not have strong causal evidence in relation to the variables under investigation. Therefore, future studies using longitudinal designs are warranted to provide additional evidence in more rigorously exploring the causal relationships between fear of COVID-19 and other mental health-related factors. Third, although the present systematic review and meta-analysis analysed 91 studies, only three of themIn conclusion, the present study found that the fear of COVID-19 had associations with a variety of mental health-related factors, from slightly weak to relatively strong magnitudes. Moreover, healthcare professionals, as compared with the general population, had stronger magnitudes in the associations between fear of COVID-19 and some mental health-related factors . Therefore, programmes on reducing fear of COVID-19 and improving mental health for both healthcare professionals and the general population are warranted during the ongoing pandemic.


Immediately following inoculation, mice were treated with or without ampicillin in drinking water for 7 days. Faeces were sampled, donor, recipient and transconjugant were enumerated, CMY-2bla abundance was determined by quantitative PCR, faecal microbial community composition was determined by 16S rRNA amplicon sequencing and cecal samples were observed histologically for evidence of inflammation. In faeces of mice that received streptomycin pre-treatment, the donor abundance remained high, and the abundance of S. Heidelberg transconjugant and the relative abundance of Enterobacteriaceae increased significantly during the ampicillin treatment. Co-blooming of the donor, transconjugant and commensal Enterobacteriaceae in the inflamed intestine promoted significantly (P<0.05) higher and possibly wider dissemination of the CMY-2bla gene in the gut microbiota of mice that received the combination of streptomycin pre-treatment and ampicillin treatment (Str–Amp) compared to the other mice. Following cessation of the ampicillin treatment, faecal shedding of S. Heidelberg transconjugant persisted much longer from mice in the Str–Amp group compared to the other mice. In addition, only mice in the Str–Amp group shed a commensal E. coli O2:H6 transconjugant, which carries three copies of the CMY-2bla gene, one on the IncI2 plasmid and two on the chromosome. The findings highlight the significance of pre-existing gut microbiota for ARG dissemination and persistence during and following antibiotic treatments of infectious diseases.Ingestion of food- or waterborne antibiotic-resistant bacteria may lead to dissemination of antibiotic resistance genes (ARGs) in the gut microbiota. The gut microbiota often suffers from various disturbances. It is not clear whether and how disturbed microbiota may affect ARG mobility under antibiotic treatments. For proof of concept, in the presence or absence of streptomycin pre-treatment, mice were inoculated orally with a  All supporting data have been provided within the article or through supplementary data files. Seven supplementary figures and four supplementary tables are available with the online version of this article. The whole-genome sequencing data generated for this study can be found in NCBI BioProject PRJNA674061.Plasmid conjugation is an effective means for bacterial dissemination of antibiotic-resistance genes (ARGs) in the gut microbiota. Early mouse studies showed conjugative transfer of ARGs in the gut under positive antibiotic selection pressure. Recent studies demonstrated ARG transfer in the absence of antibiotic selection pressure in mice with pre-diminished gut microbiota. This study was the first to explore the impacts of interaction between antibiotic selection pressure and pre-existing gut microbiota on the dynamics of conjugative transfer of ARGs. Our findings showed that the combination, compared to either one of the two factors, positive antibiotic selection pressure and pre-existing gut dysbiosis, promoted significantly higher and possibly wider dissemination of ARGs and prolonged the persistence of ARGs in the gut microbiota. This study points to a new direction for exploring pre-existing gut microbiota for better elucidation of the mechanisms of conjugative transfer of ARGs during antibiotic treatments of infectious bacterial diseases.Antimicrobial resistance  is a serious public health issue threatening the effective prevention and treatment of an ever-increasing range of bacterial infections . Long-teFirmicutes and Bacteroidetes are the dominant phyla in a healthy gut microbiota  higher than that of the control group. Although the donor abundance in the Str–Amp group was the highest among all groups at 1 day p.i., the transfer frequency of the Str–Amp group was lower than that of the Str group, likely due to limited recipient abundance  S. Heidelberg carrying an IncI2 plasmid [SH-(IncI2)], (2) S. Heidelberg carrying both an IncI1 and an IncI2 plasmids [SH-] and (3) a mouse commensal E. coli O2:H6 strain carrying both an IncI1 and an IncI2 plasmids [EC-]. EC- appeared a creamy white colour on XLT4-FR agar plates used for selective culturing S. Heidelberg transconjugant. Only SH-(IncI2) was recovered in the Amp group, both SH-(IncI2) and SH- recovered in the Str group and all three transconjugant strains recovered in the Str–Amp group  and contains no ARGs . Most of the identified genes on the IncI1 plasmid were of E. coli origin, suggesting a stable long-lived plasmid residence in E. coli. These genes are related to stress response, such as SOS response, toxin–antitoxin system and plasmid mobility, and could possibly contribute to conjugative transfer of the IncI1 plasmid. Analysis of the E.coli O2:H6 complete genome (NCBI BioSample SAMN16634233) identified two copies of the CMY-2bla gene on the chromosome and one copy on the IncI2 plasmid. Both copies of the CMY-2bla gene on the chromosome are adjacent to transposase ISEcp1 . From mice co-infected with the donor and recipient, both genes were detected for only 1 day in the control group, as the donor bacteria passed transiently through the mouse gut , suggesting clonal transmission of TEM-1Bbla along with the donor. In comparison, the abundance of CMY-2bla and E. coli O80:H26 are negligibly correlated . The dynamics of CMY-2bla and TEM-1Bbla were similar in the Amp group (CMY-2bla abundance remained high while TEM-1Bbla abundance decreased in the Str–Amp group after cessation of the ampicillin treatment (CMY-2bla to TEM-1Bbla was significantly (P<0.05) higher from 2 to 42 days p.i. in the Str–Amp group compared to the Amp group  different from the control (Tables S3 and S4). In the Str group, the relative abundance of Proteobacteria, mainly the family Enterobacteriaceae, increased on 0, 1 and 2 days p.i. and returned to normal at 7 days p.i. In the Str–Amp group, the relative abundance of Proteobacteria, mainly the family Enterobacteriaceae, increased from 0 to 7 days p.i. and returned to normal at 42 days p.i. . The gut microbial diversity was reduced by the streptomycin pre-treatment and/or ampicillin treatment . After treatment cessation, the gut microbiota gradually returned towards the original balance . The correlogram shows that the abundance of tranconjugant and CMY-2bla gene is positively correlated with the relative abundance of Proteobacteria and Enterobacteriaceae and negatively with Firmicutes, which are unlikely to act as recipients (E. coli O80:H26 and TEM-1Bbla gene are negatively correlated with the relative abundance of Firmicutes, Ruminoccoccaceae and Lachnospiraceae, and the abundance of S. Heidelberg is also negatively correlated with the relative abundance of Firmicutes.In order to determine correlations between gut microbiota and transmission of the daceae . In the ays p.i. . Expansicipients . The abuE. coli O80:H26 donor and S. Heidelberg recipient for histopathological analysis. Inflammation was observed in cecum tissue specimens from 100, 20 and 100 % of mice in the Amp, Str and Str–Amp groups, respectively (P<0.001] higher than that of the Str or control groups (Proteobacteria at 7 days p.i. Specifically, the mean inflammatory scores were 3.7, 2.6, 0.4 and 0, and the corresponding mean relative abundance of Proteobacteria was 0.8391, 0.4852, 0.0012 and 0.0002 for the Str–Amp, Amp, Str and control groups, respectively (Cecum specimens were collected at 7 days p.i. from mice co-infected with the ectively . No infll groups . These sectively .Firmicutes, more specifically Ruminoccoccaceae and Lachnospiraceae, the short-chain fatty acid producers. Thereby, the treatment would likely have lowered short-chain fatty acid concentrations, increased the luminal pH of the intestine and favoured the colonization of opportunistic pathogens [E. coli O80:H26 donor and the S. Heidelberg recipient. Colonization of the donor and recipient bacteria provided a base for bacterial cell–cell contact in the gut and facilitated conjugative transfer of the CMY-2bla gene via the IncI2 plasmid in the Str group. In comparison, in the Str–Amp group, despite benefitting the E. coli O80:H26 donor in reaching high abundance, ampicillin might kill the actively growing β-lactam-susceptible S. Heidelberg at the initial stage of infection in the pre-disturbed gut microbiota. Thus, the limited abundance of recipient might lead to a lower conjugation frequency in the Str–Amp group compared to the Str group at 1 day p.i. In support of our findings, Lopatkin et al. [in vitro bacterial culture that antibiotics may reduce conjugation frequency by reducing the sizes of either or both of the parental populations. Hall et al. [S. Heidelberg transconjugants in the Str group increased from 1 to 3 days p.i. and then decreased at 7 days p.i., while that in the Str–Amp group increased from 1 to 7 days p.i. The different dynamics suggest that carrying the IncI2 plasmid to S. Heidelberg is a cost in the absence but a benefit in the presence of ampicillin selection pressure. In addition, the relative abundance of commensal Enterobacteriaceae expanded significantly during ampicillin treatment. The simultaneous blooming of the donor, transconjugant and commensal Enterobacteriaceae in the severely inflamed mouse gut possibly built a strong base for gene transfer among these bacteria. In support of our suggestion, Stecher et al. [S. Typhimurium and mouse commensal E. coli boosted conjugative transfer of a colicin plasmid p2 from S. Typhimurium to E. coli. In our study, the CMY-2bla gene was transferred via the IncI2 plasmid to a mouse commensal E. coli O2:H6 strain and incorporated into two locations of its chromosome (et al. [E. coli O2:H6 and S. Heidelberg transconjugants, suggesting possible transfer of the plasmid from E. coli O2:H6 or other commensal bacteria to S. Heidelberg. Supporting our findings on complex conjugation among bacteria in the Str–Amp group, Conlan et al. [S. Heidelberg abundance was slightly higher in the Amp group than the Str–Amp group. The ampicillin treatment alone without bacterial infection could disturb pre-existing normal gut microbiota and reduce Firmicutes relative abundance, as shown in our previous study [S. Heidelberg might become dormant at greater colonization resistance in the Amp than Str–Amp group on 1 day p.i., and survive the ampicillin treatment under the protection of β-lactamase producing donor [S. Heidelberg reached significantly higher abundance and persisted much longer in mouse faeces following co-infection with E. coli O80:H26 compared to S. Heidelberg mono-infection. The findings suggest that antibiotic-susceptible opportunistic pathogens may exploit conjugative transfer of ARGs to propagate and persist in an otherwise hostile environment. Overall, pre-disturbed gut microbiota might promote high-abundance colonization of resistant bacteria under positive antibiotic selection pressure and encourage bacterial conjugation and spread of ARGs.To explore the impact of antibiotics on ARG mobility in pre-disturbed gut microbiota, mice were subjected to streptomycin pre-treatment. The pre-treatment decreased the relative abundance of athogens , such asn et al.  demonstrl et al.  also repr et al.  reportedromosome , likely  (et al. , such phn et al.  reportedus study . Howeverng donor . Yet, long donor . FollowiE. coli O80:H26 donor carries one copy of the CMY-2bla gene and one copy of the TEM-1Bbla gene. The abundance dynamics of the TEM-1Bbla gene and the donor was highly correlated, suggesting that the TEM-1Bbla gene might be transmitted clonally along with the donor. Supporting this suggestion, transconjugant that carries the TEM-1Bbla gene was not recovered in this and previous studies [CMY-2bla to TEM-1Bbla as an indicator for dissemination of the CMY-2bla gene, the significantly higher ratio of the two genes suggested more efficient dissemination of the CMY-2bla gene in the Str–Amp group than in the Amp group during the entire study, except 1 day p.i. The high ratios might be attributed to the transfer of the CMY-2bla gene to S. Heidelberg and commensal E. coli, the incorporation of the CMY-2bla gene into the commensal E. coli chromosome and possible dissemination of the CMY-2bla gene in the gut microbiota. Furthermore, following cessation of the ampicillin treatment, the abundance of the CMY-2bla gene remained high, even though the abundance of the donor and transconjugant decreased significantly in the Str–Amp group, suggesting possible persistence of the CMY-2bla gene in the gut microbiota at no selective advantage.The  studies . Using tCMY-2bla gene from the E. coli O80:H26 donor to S. Heidelberg, commensal E. coli and possibly other commensal Enterobacteriaceae under positive ampicillin selection pressure. Following cessation of ampicillin treatment, shedding of the S. Heidelberg and E. coli transconjugants persisted over 35 days. These findings underline the importance of pre-existing gut microbiota on dissemination of ARGs during antibiotic treatments of bacterial infection.In this study, pre-disturbed gut microbiota promoted conjugative transfer of the Click here for additional data file.